SUMMARYThis paper proposes an improved reinitialized social structures particle swarm optimization (IRS-PSO) for solving optimal multiple distributed generations (DG) placement in a microgrid (MG) system. The movement of each particle in IRS-PSO is pulled by an inertia term, a cognitive term (personal best), and three social learning terms including global best, local best, and near neighbor best. The objective is to minimize the real power loss within real and reactive power generation limits and voltage limits. Five types in a MG system are considered including MG with DG supplying real power only, MG with DG supplying reactive power only, MG with DG supplying real power and consuming reactive power, MG with DG supplying real power and reactive power, and MG with four different types of DG regulating the bus voltage. For a given number of DG units in each type, IRS-PSO can find better sizes and locations of multiple DGs than repetitive load flow, basic particle swarm optimization (BPSO), adaptive weight particle swarm optimization (APSO), and global best, local and near neighbor best particle swarm optimization (GLN-PSO) on the 69-bus radial MG distribution system.
SUMMARYThis paper proposes an improved binary multi-objectives particle swarm optimization (IB-MOPSO) for solving optimal multiple protective devices placement using improved reliability model in a microgrid (MG) system. The multi-objectives are to minimize system average interruption frequency index, system average interruption duration index, and total cost including investment and interruption cost. Binary multi-objectives PSO (B-MOPSO) is enhanced by using a bell shape function and three particle movement strategies including global guidance located in the least crowded areas, perturbation with different evolution method, and coverage of unexplored search space in the non-dominated front. For MG planning, IB-MOPSO can find better locations and number of protective devices including reclosers, switches, and fuses than B-MOPSO and ant colony optimization on the 51 section Provincial Electricity Authority of Thailand MG distribution system.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.